From May 2011 and November 2011, a population-based cross-sectional survey (Chongming Health Investigation) was conducted in Chongming District, Shanghai, China. A two-stage stratified sampling method was used. First, 12 residential communities or streets were randomly selected from the Chongming District. Of these, 8 urban communities and 4 rural communities were chosen to represent people with high to low socioeconomic status. Secondly, Within each community/street, all eligible individuals were sampled, with the exception that in households with more than one eligible individual, one individual was randomly selected. During the recruiting phase, inhabitants aged ≥40 years in these 12 communities were invited by telephone or door-to-door visit to participate in this study. A total of 9,930 subjects completed the survey, yielding a response rate of 92.4%. Each participant signed an informed consent form before completing the questionnaire. The protocol was approved by the Institutional Review Board of Xinhua Hospital affiliated with Shanghai Jiao-Tong University School of Medicine.After excluding subjects with missing data regarding serum uric acid (n = 1194) or coronary heart disease (n = 129) or stroke (n = 97), 8510 participants were included in the final analysis (Figure 1).

A standardized questionnaire was used by trained physicians to collect information such as age, sex, medications, education level (6, 7–9, or ≥10 years in school). The history of chronic diseases and current use of medications were recorded. The smoking or alcohol consumption habit was defined as never, current (smoking or consuming alcohol regularly in the past 6 months), or ever (cessation of smoking or alcohol consumption for more than 6 months). The type, amount, and frequency of alcohol consumption were collected. Based on the alcohol content of the beverages reported, mean daily alcohol consumption was calculated and expressed in grams per day. Physical activity at leisure time was estimated using the short form of the International Physical Activity Questionnaire by adding questions on frequency and duration of moderate and vigorous activities and walking [22].

Anthropometric measurements were performed by the trained personnel using a standardized protocol. Height was measured to the nearest 0.1 cm, and weight was recorded to the nearest 0.1 kg while participants were wearing lightweight clothing and no shoes. Body mass index (BMI) was defined as body weight in kilograms divided by height squared in meters. Waist circumference (WC) was measured to the nearest 0.1 cm at the umbilical level with the participant in a standing position. Hip circumference was measured over the widest part of the gluteal region, and the waist-to-hip ratio was calculated as a measure of central obesity. Three blood pressure recordings were obtained from the right arm of patients in a sitting position after 30 min of rest; measurements were taken in 5-min intervals, and mean values were calculated.

Peripheral venous blood samples were collected after an overnight fast. The fasting glucose, glucose 2 h after oral glucose tolerance test were measured with the use of the glucose oxidase method on an autoanalyzer (Modular P800; Roche, Basel, Switzerland). Triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), and serum uric acid were measured using chemiluminescence methods on the autoanalyzer (Modular E170; Roche). Glycated hemoglobin(HbA1c) was measured with the use of the Chromatography method on an autoanalyzer (D10; Bio-Rad, USA).

Hypertension was defined as diastolic blood pressure ≥90 mm Hg, systolic blood pressure of ≥140 mm Hg, or current medication for hypertension (as defined by WHO 1999) [16]. Coronary heart disease (CHD) and stroke were defined using the WHO MONICA criteria [23]. Myocardial infarction was diagnosed by a representative set of electrocardiogram, cardiac enzyme values, and typical symptoms. Angina was defined as use of nitroglycerine, experience of typical chest pain, and electrocardiogram changes compatible with ischemic heart disease. Strokes were defined as events requiring hospitalization; this information was verified from local hospital records, and 82% of the cases were confirmed using computed tomography and magnetic resonance imaging. Cardiovascular disease in the present study was defined by the presence of one or more of these two outcomes: CHD and stroke. Subjects with a fasting plasma glucose level of 7.0 mmol/l and/or a 2-h plasma glucose level of 11.1 mmol/l during an oral glucose tolerance test and/or who were receiving antidiabetic medications were diagnosed with diabetes mellitus. The diagnosis of cardiovascular events was based on self-reports, confirmed by hospital medical records and further clinical examinations carried out at the time of the survey (including electrocardiogram and ankle-arm systolic blood pressure index).

The MetS was defined based upon the updated NCEP-ATPIII for Asian Americans [24] as presenting 3 or more of the following components: 1) waist cirumference ≥90 cm for men or ≥80 cm for women; 2) triglycerides ≥1.7 mmol/l; 3) HDL cholesterol <1.03 mmol/l for men or <1.30 mmol/l for women; 4) blood pressure ≥130/85 mm Hg or current use of anti-hypertensive medications; and 5) fasting glucose ≥5.6 mmol/l or previously diagnosed type 2 diabetes or on oral antidiabetic agents or insulin.

Normally distributed data were expressed as means ± SD, whereas variables with a skewed distribution were reported as median (interquartile range) and log transformed to approximate normality before analysis. Categorical variables were represented by frequency and percentage. The association of demographic, medical, metabolic and clinical characteristics with serum uric acid quartiles was assessed using multivariate linear or logistic regression analyses, adjusting for age and gender, for continuous and dichotomous variables, respectively. The correlations among serum uric acid, anthropometric indices and metabolic features adjusting for age and gender were obtained using Spearman partial correlation analysis. Sampling weights was used when estimating prevalence of CVD. The trend for age- and sex-adjusted prevalence of CVD according to quartile of uric acid and the presence of metabolic syndrome were analysed using linear regression model. Multivariate logistic regression models were used to estimate the odds ratios (ORs) for CHD, stroke and CVD. Potential confounding variables including age, gender, smoking, alcohol drinking, physical activity, educational level, education, BMI, and metabolic syndrome were controlled in the regression models. All statistical analysis were performed with the SPSS Statistical Package (version 15.0; SPSS Inc., Chicago, IL). P < 0.05 was considered statistically significant.

Included were 8510 individuals who had both uric acid and CVD assessments (Figure 1). The mean age of this cohort was 55.90 ± 7.89 years, and approximately 32% were men. Baseline demographic and medical characteristics for both genders combined and divided by uric acid quartiles are presented in Table 1. Higher uric acid levels were associated with higher proportion of metabolic syndrome, proportion of men, age, smoking, alcohol consumption, systolic blood pressure, diastolic blood pressure, BMI, waist circumference, hip circumference, waist to hip ratio, fasting plasma glucose, postprandial 2-hour plasma glucose, glycohemoglobin, triglycerides, total cholesterol, LDL-cholesterol, presence of stroke, presence of CHD, hypertension, diabetes (all P < 0.05). In contrast, the patients with higher uric acid levels displayed lower levels of HDL cholesterol (P < 0.001) (Table 1).

Partial Spearman correlation analysis demonstrated the strongest correlation between uric acid and triglycerides among various metabolic features (Table 2). Moreover there was strong partial correlation between uric acid and BMI, TC, Waist circumference (WC), systolic blood pressure (SBP) and diastolic blood pressure (DBP), adjusting for age and gender, (all P < 0.001) (Table 2). As presented in Table 3, the ORs for CHD, stroke and CVD were higher with increasing uric acid quartiles (all p < 0.001 for linear trend). In the highest uric acid quartile, the adjusted ORs of CHD, stroke and CVD were 2.34 (95% confidence interval [CI] 1.73 to 3.45), 2.18 (95% CI 1.86 to 3.27), and 2.16 (95% CI 1.80 to 3.29), respectively, compared with those in the first quartile of UA (Table 3).We further analyzed the prevalence of CVD according to quartile of uric acid and the presence of metabolic syndrome. After adjustments for age, gender, alcohol drinking, smoking, education, physical activity, TC, LDL, the prevalence of CVD in subjects with metabolic syndrome increased with uric acid quartile (p < 0.001 for linear trend) (Figure 2). No trend was observed in subject without metabolic syndrome (p = 0.217 for linear trend).